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Table · dataset · 2023

Classifying Fermi-LAT gamma-ray sources

Listed in IVOA Registry (Virtual Observatory)

Machine learning is an automatic technique that is revolutionizing scientific research, with innovative applications and wide use in astrophysics.

Description

The aim of this study was to develop an optimized version of an Artificial Neural Network machine learning method for classifying blazar candidates of uncertain type detected by the Fermi Large Area Telescope {gamma}-ray instrument. The final result of this study increased the classification performance by about 80 per cent with respect to previous method, leaving only 15 unclassified blazars out of 573 blazar candidates of uncertain type listed in the LAT 4-year Source Catalog.

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Topics

Stated by source
Gamma-Ray · Radio · X-Ray
Inferred from text
Astronomical sciences 71%
Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
IVOA Registry (Virtual Observatory)ivo://cds.vizier/j/mnras/490/477012 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · IVOA Registryconnector:ivoa_registry@1.0.0
concepts[field].anzsrc:group:5101enrichment · IVOA Registrytaxonomy-embedding@1.1.0title+keywords+description (71%)
concepts[field].local:field:astronomymapping · IVOA Registryconnector:ivoa_registry@1.0.0
concepts[modality].ivoa_waveband:gamma-raysource · IVOA Registryconnector:ivoa_registry@1.0.0
concepts[modality].ivoa_waveband:radiosource · IVOA Registryconnector:ivoa_registry@1.0.0
concepts[modality].ivoa_waveband:x-raysource · IVOA Registryconnector:ivoa_registry@1.0.0
descriptionsource · IVOA Registryconnector:ivoa_registry@1.0.0rr.resource.res_description
license_textsource · IVOA Registryconnector:ivoa_registry@1.0.0
publication_datesource · IVOA Registryconnector:ivoa_registry@1.0.0
titlesource · IVOA Registryconnector:ivoa_registry@1.0.0rr.resource.res_title
updated_datesource · IVOA Registryconnector:ivoa_registry@1.0.0